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The 'medical examination' to which abductees are said to be subjected, often accompanied by sadistic sexual manipulation, is reminiscient of the medieval tales of encounters with demons. It makes no sense in a sophisticated or technical framework: any intelligent being equipped with the scientific marvels that UFOs possess would be in a position to achieve any of these alleged scientific objectives in a shorter time and with fewer risks.
Von Neumann languages do not have useful properties for reasoning about programs. Axiomatic and denotational semantics are precise tools for describing and understanding conventional programs, but they only talk about them and cannot alter their ungainly properties. Unlike von Neumann languages, the language of ordinary algebra is suitable both for stating its laws and for transforming an equation into its solution, all within the "language."
Most programs are not write-once. They are reworked and rewritten again and again in their lived. Bugs must be debugged. Changing requirements and the need for increased functionality mean the program itself may be modified on an ongoing basis. During this process, human beings must be able to read and understand the original code. It is therefore more important by far for humans to be able to understand the program than it is for the computer.
When you write a program, think of it primarily as a work of literature. You're trying to write something that human beings are going to read. Don't think of it primarily as something a computer is going to follow. The more effective you are at making your program readable, the more effective it's going to be: You'll understand it today, you'll understand it next week, and your successors who are going to maintain and modify it will understand it.
The reason for teaching history is not that it changes society, but that it changes pupils; it changes what they see in the world, and how they see it.... To say someone has learnt history is to say something very wide ranging about the way in which he or she is likely to make sense of the world. History offers a way of seeing almost any substantive issue in human affairs, subject to certain procedures and standards, whatever feelings one may have.
The Web took off in all its glory because it was a royalty-free infrastructure . . . When I invented the Web, I didn't have to ask anyone's permission. Now, hundreds of millions of people are using it freely. I am worried that that is going to end in the U.S.A. If we had a situation in which the U.S. had serious flaws in its Net Neutrality, and Europe did have Net Neutrality, and I were trying to start a company, then I would be very tempted to move.
In 1905, when you went motoring, you took your mechanic. Twenty-five years later, mass production revolutionized the role of the automobile, but buying a Ford wouldn't have made sense if everyone still needed a mechanic on board. In 1955, when you used your computer, you took your programmer. Twenty-five years later, mass production revolutionized the role of the computer, but buying a micro wouldn't have made sense if everyone still needed a programmer.
When I came back from Munich, it was September, and I was Professor of Mathematics at the Eindhoven University of Technology. Later I learned that I had been the Department's third choice, after two numerical analysts had turned the invitation down; the decision to invite me had not been an easy one, on the one hand because I had not really studied mathematics, and on the other hand because of my sandals, my beard and my "arrogance" (whatever that may be).
It has long been my personal view that the separation of practical and theoretical work is artificial and injurious. Much of the practical work done in computing, both in software and in hardware design, is unsound and clumsy because the people who do it have not any clear understanding of the fundamental design principles of their work. Most of the abstract mathematical and theoretical work is sterile because it has no point of contact with real computing.
When certain concepts of TeX are introduced informally, general rules will be stated; afterwards you will find that the rules aren't strictly true. In general, the later chapters contain more reliable information than the earlier ones do. The author feels that this technique of deliberate lying will actually make it easier for you to learn the ideas. Once you understand a simple but false rule, it will not be hard to supplement that rule with its exceptions.
Skeptics, who flatly deny the existence of any unexplained phenomenon in the name of 'rationalism,' are among the primary contributors to the rejection of science by the public. People are not stupid and they know very well when they have seen something out of the ordinary. When a so-called expert tells them the object must have been the moon or a mirage, he is really teaching the public that science is impotent or unwilling to pursue the study of the unknown.
Our intellectual powers are rather geared to master static relations and that our powers to visualize processes evolving in time are relatively poorly developed. For that reason we should do (as wise programmers aware of our limitations) our utmost to shorten the conceptual gap between the static program and the dynamic process, to make the correspondence between the program (spread out in text space) and the process (spread out in time) as trivial as possible.
The artificial intelligence approach may not be altogether the right one to make to the problem of designing automatic assembly devices. Animals and machines are constructed from entirely different materials and on quite different principles. When engineers have tried to draw inspiration from a study of the way animals work they have usually been misled; the history of early attempts to construct flying machines with flapping wings illustrates this very clearly.
One is faced with a dilemma: If one places total trust in all other users, one is vulnerable to the antisocial behavior of any malicious user consider the case of viruses. But if one tries to be totally reclusive and isolated, one is not only bored, but one's information universe will cease to grow and be enhanced by interaction with others. The result is that most of us operate in a complicated trade-off zone with various arrangements of trust and security mechanisms.
The Open Source theorem says that if you give away source code, innovation will occur. Certainly, Unix was done this way... However, the corollary states that the innovation will occur elsewhere. No matter how many people you hire. So the only way to get close to the state of the art is to give the people who are going to be doing the innovative things the means to do it. That's why we had built-in source code with Unix. Open source is tapping the energy that's out there.
Progress in computer science is made with the distribution of revolutionary software systems and the publication of revolutionary books. We don't need a fancy information system to alert us to these grand events; they will hit us in the face. Another good excuse for ignoring the literature is that, since everyone has strong beliefs about fundamentals but can't support those beliefs rationally or consistently convince non-believers, computer science is actually a religion.
If you stay up late and you have another hour of work to do, you can just stay up another hour later without running into a wall and having to stop. Whereas it might take three or four hours if you start over, you might finish if you just work that extra hour. If you're a morning person, the day always intrudes a fixed amount of time in the future. So it's much less efficient. Which is why I think computer people tend to be night people - because a machine doesn't get sleepy.
Industrial production, the flow of resources in the economy, the exertion of military effort in a war, the management of finances --all require the coordination of interrelated activities. What these complex undertakings share in common is the task of constructing a statement of actions to be performed, their timing and quantity (called a program or schedule), that, if implemented, would move the system from a given initial status as much as possible towards some defined goal
Complexity has and will maintain a strong fascination for many people. It is true that we live in a complex world and strive to solve inherently complex problems, which often do require complex mechanisms. However, this should not diminish our desire for elegant solutions, which convince by their clarity and effectiveness. Simple, elegant solutions are more effective, but they are harder to find than complex ones, and they require more time, which we too often believe to be unaffordable
...methods are more important than facts. The educational value of a problem given to a student depends mostly on how often the thought processes that are invoked to solve it will be helpful in later situations. It has little to do with how useful the answer to the problem may be. On the other hand, a good problem must also motivate the students; they should be interested in seeing the answer. Since students differ so greatly, I cannot expect everyone to like the problems that please me.
Although mathematical notation undoubtedly possesses parsing rules, they are rather loose, sometimes contradictory, and seldom clearly stated. [...] The proliferation of programming languages shows no more uniformity than mathematics. Nevertheless, programming languages do bring a different perspective. [...] Because of their application to a broad range of topics, their strict grammar, and their strict interpretation, programming languages can provide new insights into mathematical notation.
The book Dynamic Programming by Richard Bellman is an important, pioneering work in which a group of problems is collected together at the end of some chapters under the heading "Exercises and Research Problems," with extremely trivial questions appearing in the midst of deep, unsolved problems. It is rumored that someone once asked Dr. Bellman how to tell the exercises apart from the research problems, and he replied: "If you can solve it, it is an exercise; otherwise it's a research problem."
There is a race between the increasing complexity of the systems we build and our ability to develop intellectual tools for understanding their complexity. If the race is won by our tools, then systems will eventually become easier to use and more reliable. If not, they will continue to become harder to use and less reliable for all but a relatively small set of common tasks. Given how hard thinking is, if those intellectual tools are to succeed, they will have to substitute calculation for thought.
Much of the early engineering development of digital computers was done in universities. A few years ago, the view was commonly expressed that universities had played their part in computer design, and that the matter could now safely be left to industry. [...] Apart from the obvious functions of keeping in the public domain material that might otherwise be hidden, universities can make a special contribution by reason of their freedom from commercial considerations, including freedom from the need to follow the fashion.
Another effective [debugging] technique is to explain your code to someone else. This will often cause you to explain the bug to yourself. Sometimes it takes no more than a few sentences, followed by an embarrassed "Never mind, I see what's wrong. Sorry to bother you." This works remarkably well; you can even use non-programmers as listeners. One university computer center kept a teddy bear near the help desk. Students with mysterious bugs were required to explain them to the bear before they could speak to a human counselor.
At first I hoped that such a technically unsound project would collapse but I soon realized it was doomed to success. Almost anything in software can be implemented, sold, and even used given enough determination. There is nothing a mere scientist can say that will stand against the flood of a hundred million dollars. But there is one quality that cannot be purchased in this way - and that is reliability. The price of reliability is the pursuit of the utmost simplicity. It is a price which the very rich find most hard to pay.
I was appalled to find that the mathematical notation on which I had been raised failed to fill the needs of the courses I was assigned, and I began work on extensions to notation that might serve. In particular, I adopted the matrix algebra used in my thesis work, the systematic use of matrices and higher-dimensional arrays (almost) learned in a course in Tensor Analysis rashly taken in my third year at Queen's, and (eventually) the notion of Operators in the sense introduced by Heaviside in his treatment of Maxwell's equations.
In the Java world, security is not viewed as an add-on a feature. It is a pervasive way of thinking. Those who forget to think in a secure mindset end up in trouble. But just because the facilities are there doesn't mean that security is assured automatically. A set of standard practices has evolved over the years. The Secure Coding Standard for Java is a compendium of these practices. These are not theoretical research papers or product marketing blurbs. This is all serious, mission-critical, battle-tested, enterprise-scale stuff.
I think the stage is set for the appearance of new faiths, centred on the UFO belief. To a greater degree than all phenomena modern science is confronting, the UFO can inspire awe, the sense of the smallness of man, and an idea of the possibility of contact with the cosmic. The religions we have briefly surveyed began with the miraculous experiences of one person, but to-day there are thousands for whom the belief in otherworldly contact is based on intimate conviction, drawn from what they regard as personal contact with UFOs and their occupants.
What is the central core of the subject [computer science]? What is it that distinguishes it from the separate subjects with which it is related? What is the linking thread which gathers these disparate branches into a single discipline. My answer to these questions is simple -it is the art of programming a computer. It is the art of designing efficient and elegant methods of getting a computer to solve problems, theoretical or practical, small or large, simple or complex. It is the art of translating this design into an effective and accurate computer program.
...Simplifications have had a much greater long-range scientific impact than individual feats of ingenuity. The opportunity for simplification is very encouraging, because in all examples that come to mind the simple and elegant systems tend to be easier and faster to design and get right, more efficient in execution, and much more reliable than the more contrived contraptions that have to be debugged into some degree of acceptability....Simplicity and elegance are unpopular because they require hard work and discipline to achieve and education to be appreciated.
When I first prepared this particular talk... I realized that my usual approach is usually critical. That is, a lot of the things that I do, that most people do, are because they hate something somebody else has done, or they hate that something hasn't been done. And I realized that informed criticism has completely been done in by the web. Because the web has produced so much uninformed criticism. It's kind of a Gresham's Law-bad money drives the good money out of circulation. Bad criticism drives good criticism out of circulation. You just can't criticize anything.
What I realized is that if we're going to be able to have a theory about what happens in, for example, nature there has to ultimately be some rule by which nature operates. But the issue is does that rule have to correspond to something like a mathematical equation, something that we have sort of created in our human mathematics? And what I realized is that now with our understanding of computation and computer programs and so on, there is actually a much bigger universe of possible rules to describe the natural world than just the mathematical equation kinds of things.
...One of the most important lessons, perhaps, is the fact that SOFTWARE IS HARD. From now on I shall have significantly greater respect for every successful software tool that I encounter. During the past decade I was surprised to learn that the writing of programs for TeX and Metafont proved to be much more difficult than all the other things I had done (like proving theorems or writing books). The creation of good software demand a significiantly higher standard of accuracy than those other things do, and it requires a longer attention span than other intellectual tasks.
Yes, I share your concern: how to program well -though a teachable topic- is hardly taught. The situation is similar to that in mathematics, where the explicit curriculum is confined to mathematical results; how to do mathematics is something the student must absorb by osmosis, so to speak. One reason for preferring symbol-manipulating, calculating arguments is that their design is much better teachable than the design of verbal/pictorial arguments. Large-scale introduction of courses on such calculational methodology, however, would encounter unsurmoutable political problems.
I think that it's extraordinarily important that we in computer science keep fun in computing. When it started out, it was an awful lot of fun. Of course, the paying customers got shafted every now and then, and after a while we began to take their complaints seriously. We began to feel as if we really were responsible for the successful, error-free perfect use of these machines. I don't think we are. I think we're responsible for stretching them, setting them off in new directions, and keeping fun in the house. I hope the field of computer science never loses its sense of fun.